File size: 3,928 Bytes
ea81da4 3c6c6c9 ea81da4 3c6c6c9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: whisper-large-v2-multilingual
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-large-v2-multilingual
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3502
- Wer Eng: 0.01
- Wer Lug: 0.106
- Wer Ach: 0.241
- Wer Lgg: 0.361
- Wer Teo: 0.327
- Wer Nyn: 0.387
- Wer Mean: 0.239
- Cer Eng: 0.004
- Cer Lug: 0.029
- Cer Ach: 0.064
- Cer Lgg: 0.118
- Cer Teo: 0.145
- Cer Nyn: 0.125
- Cer Mean: 0.081
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Eng | Wer Lug | Wer Ach | Wer Lgg | Wer Teo | Wer Nyn | Wer Mean | Cer Eng | Cer Lug | Cer Ach | Cer Lgg | Cer Teo | Cer Nyn | Cer Mean |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:--------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:--------:|
| 1.0754 | 0.1 | 200 | 0.6042 | 0.031 | 0.267 | 0.428 | 0.481 | 0.615 | 0.712 | 0.422 | 0.017 | 0.053 | 0.121 | 0.147 | 0.242 | 0.201 | 0.13 |
| 0.5269 | 1.0001 | 400 | 0.4731 | 0.018 | 0.176 | 0.34 | 0.422 | 0.45 | 0.531 | 0.323 | 0.008 | 0.04 | 0.093 | 0.126 | 0.174 | 0.156 | 0.099 |
| 0.4203 | 1.1001 | 600 | 0.4230 | 0.018 | 0.199 | 0.319 | 0.416 | 0.418 | 0.482 | 0.309 | 0.007 | 0.06 | 0.094 | 0.122 | 0.163 | 0.146 | 0.099 |
| 0.3851 | 2.0002 | 800 | 0.3871 | 0.014 | 0.116 | 0.271 | 0.374 | 0.443 | 0.454 | 0.279 | 0.006 | 0.03 | 0.073 | 0.11 | 0.19 | 0.137 | 0.091 |
| 0.3241 | 2.1002 | 1000 | 0.3716 | 0.015 | 0.12 | 0.271 | 0.392 | 0.397 | 0.416 | 0.269 | 0.006 | 0.03 | 0.077 | 0.133 | 0.166 | 0.127 | 0.09 |
| 0.3161 | 3.0004 | 1200 | 0.3584 | 0.021 | 0.121 | 0.269 | 0.429 | 0.36 | 0.38 | 0.263 | 0.008 | 0.032 | 0.071 | 0.154 | 0.16 | 0.121 | 0.091 |
| 0.2764 | 3.1004 | 1400 | 0.3546 | 0.012 | 0.116 | 0.254 | 0.376 | 0.348 | 0.403 | 0.251 | 0.004 | 0.03 | 0.073 | 0.123 | 0.155 | 0.125 | 0.085 |
| 0.2692 | 4.0005 | 1600 | 0.3487 | 0.011 | 0.107 | 0.248 | 0.352 | 0.336 | 0.377 | 0.238 | 0.004 | 0.029 | 0.067 | 0.102 | 0.15 | 0.123 | 0.079 |
| 0.2427 | 4.1005 | 1800 | 0.3535 | 0.01 | 0.113 | 0.24 | 0.384 | 0.329 | 0.387 | 0.244 | 0.004 | 0.03 | 0.066 | 0.122 | 0.145 | 0.125 | 0.082 |
| 0.2413 | 5.0006 | 2000 | 0.3502 | 0.01 | 0.106 | 0.241 | 0.361 | 0.327 | 0.387 | 0.239 | 0.004 | 0.029 | 0.064 | 0.118 | 0.145 | 0.125 | 0.081 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.1
- Datasets 2.21.0
- Tokenizers 0.19.1
|